Issue |
Int. J. Metrol. Qual. Eng.
Volume 12, 2021
Topical Issue - Advances in Metrology and Quality Engineering
|
|
---|---|---|
Article Number | 21 | |
Number of page(s) | 11 | |
DOI | https://doi.org/10.1051/ijmqe/2021018 | |
Published online | 26 August 2021 |
Research article
Maintenance decision method considering inspection of mining equipment
1
School of Mechanical Engineering, Xi'an University of Science and Technology 710054, PR China
2
School of Mechanical and Aerospace Engineering, Brunel University London, London UB8 3PH, UK
* Corresponding author: 582060393@qq.com
Received:
12
November
2020
Accepted:
8
July
2021
In coal mining industry, equipment safety and reliability during operation are essential in the production process. In recent years, along with the continuous improvement of intelligent coal mining equipment, reliable production requirements have simultaneously increased. Therefore, this article aims to study the maintenance decision making method that considers the safety inspection of a fully mechanized mining equipment group. The goal is to establish a maintenance decision making model that considers the safety overhaul of fully mechanized mining equipment group in order to minimize the total maintenance, production costs and safety risks. Firstly, the regular safety inspection procedure and the maintenance process were introduced. Then, a model guideline method that considers a fully mechanized mining equipment group's safety inspection was established. Finally, through the comparison of algorithms and maintenance strategies, it is proved that the maintenance decision optimization method proposed in this paper is of great significance for improving equipment reliability, improving comprehensive operation rate, reducing maintenance costs, and ensuring coal mine safety production.
Key words: Comprehensive mining equipment group / maintenance decision making / cost / safety / genetic algorithm
© X.G. Cao et al., Published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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